Following a rigorous methodology is key to delivering customer satisfaction and expanding analytics use cases across the business.
During the planning phase, key business and technology stakeholders determine the business drivers, objectives, and goals.
Establishing a 360 solution can at first can seem daunting. There are many use cases which can be achieved, such as:
Considerations may need to be practical/tactical in the early milestones on the 360 solution roadmap. These must still meet business needs and deliver on value in manageable chunks. Selection of data sources and consumers needs to be planned as part of this exercise.
Communication throughout the planning process is key. Ensure that all stakeholders understand the goals and how it impacts them and that the business case is solid. Modify the expected outcomes based on feedback.
Data stewardship is also key. It’s critical to fully understand the data regulatory requirements that impact the project. Organizations need a thorough understanding of data usage, planned applications, and governance requirements, which determines the levels of security and access control to meet corporate data privacy policies as well as laws.
The next step is to develop the solution architecture, including technical requirements, volume requirements, and integration patterns. Determine the functional requirements for the project. Determine the applications which need to comprise the solution, which may need to include analytic applications to consume the mastered data to generate reports. Consider how users and applications will consume and analyze information and the development requirements.
Design and build processes to ensure data quality and to integrate data from source applications. Determine the integration needs for each source application. Data profiling is a critical exercise to execute. Focusing on the source attributes which will be used in the 360 solution profile the data across all of the data quality measures and present the analysis per source to the subject matter experts to gain insights into the data. Assess your master data management strategy, identifying any gaps and developing a model and architecture for data management.
Assess your organization’s resources to understand what skills you will need and where the gaps are. Establish the project rolesfor data analysts, developers, systems administrators, enterprise architect, data steward, and project manager. Identify where you might need new skills or consultant assistance and develop a detailed project plan.
Success
Link Copied to Clipboard